Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. As such, NLP is related to the area of human-computer interaction. Many challenges in NLP involve natural language understanding—that is, enabling computers to derive meaning from human or natural language input.
A known approach in creating NLP systems is to train several statistical models configured to classify a particular natural language query into a category, as well as using other statistical models to perform named entity recognition on the query to extract atomic elements referred to as entities. One shortcoming with this approach is that classification may require significant computing resources (and hence, computing time) in order to classify between a large number of categories.
Another such problem with NLP approaches that use statistical models is that statistical models may have difficulty classifying certain queries correctly when a few words in the query can significantly alter its meaning. Similar queries may be classified into the same domain, when one query should be classified into a particular domain and the other query should be classified into a different domain.